Applied Statistics for Scientists and Engineers 2017
- Start Date:
- Thursday, 2 March, 2017
- End Date:
- Friday, 3 March, 2017 6:00pm
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Course "Applied Statistics for Scientists and Engineers" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.Overview: Throughout 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries, the application of statistical methods are specified for: setting validation criteria and specifications, performing measurement systems analysis (MSA), conducting stability analysis, using design of experiment (DOE) for process development and validation, developing process control charts, and determining process capability indices.
Different statistical methods are required for each of these particular applications. Data and tolerance intervals are common tools used for setting acceptance criteria and specifications. Simple linear regression and analysis-of-covariance (ANCOVA) are used for setting expiries and conducting stability analysis studies. Two-sample hypothesis tests, analysis-of-variance (ANOVA), regression, and ANCOVA are methods used for analyzing designed experiment for process development and validation studies.
Descriptive statistics (distribution, summary statistics), run charts, and probability (distributions) are used for developing process control charts and developing process capability indices. This course provides instruction on how to apply the appropriate statistical approaches: descriptive statistics, data intervals, hypothesis testing, ANOVA, regression, ANCOVA, and model building. Once competence in each of these areas is established, industry-specific applications are presented for the participants.Why should you attend?21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries specify the application of statistical methods across the product quality lifecycle.According to the Quality System Regulation (QSR) for medical devices, "Where appropriate, each manufacturer shall establish and maintain procedures for identifying valid statistical techniques required for establishing, controlling, verifying the acceptability of process capability and product characteristics." Although there are many statistical method that may be applied to satisfy this portion of the QSR, there are some commonly accepted methods that all companies can and should be using to develop acceptance criteria, to ensure accurate and precise measurement systems, to fully characterize manufacturing processes, to monitor and control process results and to select an appropriate number of samples.According to both 21 CFR and guidance documents, the need for statistical methods is well established from discovery through product discontinuation. 21 CFR specifies the "the application of suitable statistical procedures" to establish both in-process and final specifications.
The guidance documents necessitate the application of statistical methods for development and validation of measurement systems, process understanding using Quality by Design (QbD) principles, process validation, as well as ensuring the manufacturing process is in control and is capable.This course provides instruction statistical methods for data analysis of applications related to the pharmaceutical, biopharmaceutical, and medical device industries.Areas Covered in the Session:Objectives:describe and analyze the distribution of datadevelop summary statisticsgenerate and analyze statistical intervals and hypothesis tests to make data-driven decisionsdescribe the relationship between and among two or more factors or responsesunderstand issues related to sampling and calculate appropriate sample sizesuse statistical intervals to setting specifications/develop acceptance criteriause Measurement Systems Analysis (MSA) to estimate variance associated with: repeatability, intermediate precision, and reproducibilityensure your process is in (statistical) control and capable Who will benefit:This seminar is designed for pharmaceutical, biopharmaceutical, and medical device professionals who are involved with product and/or process design:Process Scientist/EngineerDesign EngineerProduct Development EngineerRegulatory/Compliance ProfessionalDesign Controls EngineerSix Sigma Green BeltSix Sigma Black BeltContinuous Improvement ManagerAgenda:Day 1 ScheduleLecture 1:Basic Statisticssample versus populationdescriptive statisticsdescribing a distribution of valuesLecture 2:Intervalsconfidence intervalsprediction intervalstolerance intervalsLecture 3:Hypothesis Testingintroducing hypothesis testingperforming means testsperforming normality tests and making non-normal data normalLecture 4:ANOVAdefining analysis of variance and other terminologydiscussing assumptions and interpretationinterpreting hypothesis statements for ANOVAperforming one-way ANOVAperforming two-way ANOVADay 2 ScheduleLecture 1:Regression and ANCOVAproducing scatterplots and performing correlationperforming simple linear regressionperforming multiple linear regressionperforming ANCOVAusing model diagnosticsLecture 2:Applied Statisticssetting specificationsMeasurement Systems Analysis (MSA) for assaysstability analysisintroduction to design of experiments (DOE)process control and capabilitypresenting results Speaker: Heath RushingCo-founder and Principal, AdsurgoHeath Rushing is the cofounder of Adsurgo and author of the book Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP.
Previously, he was the JMP and Six Sigma training manager at SAS. He led a team of nine technical professionals designing and delivering applied statistics and quality continuing education courses. He created tailored courses, applications, and long-term training plans in quality and statistics across a variety of industries to include biotech, pharmaceutical, medical device, and chemical processing. Mr. Rushing has been an invited speaker on applicability of statistics for national and international conferences.
As a Quality Engineer at Amgen, he championed statistical principles in every business unit. He designed and delivered a DOE course that immediately became the company standard required at multiple sites. Additionally, he developed and implemented numerous innovative statistical methods advancing corporate risk management, process capability, and validation acceptance criteria. He won the top teaching award out of 54 instructors in the Air Force Academy math department where he taught several semesters and sections of operations research and statistics.
Additionally, he designs and delivers short courses in statistics, data mining, and simulation modeling for SAS. Location: SFO, CA Date: March 2nd & 3rd, 2017 and Time: 9:00 AM to 6:00 PM Venue: DoubleTree by Hilton Hotel San Francisco AirportAddress: 835 Airport Blvd., Burlingame CA 94010-9949 Price: Price: $1,295.00 (Seminar Fee for One Delegate)Until January 20, Early Bird Price: $1,295.00 from January 21 to February 28, Regular Price: $1,495.00Register for 5 attendees Price: $3,885.00 $6,475.00 You Save: $2,590.00 (40%)*Quick Contact:NetZealous DBA as GlobalCompliancePanel Phone: 1-800-447-9407Fax: 302-288-6884Email: firstname.lastname@example.org
DoubleTree by Hilton Hotel San Francisco Airport 835 Airport Blvd.,
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